alibaba/open-code-review：README 來源編輯指南

alibaba/open-code-review 的 README 將專案描述為「Fast, efficient, battle-tested at Alibaba's scale. Hybrid architecture code review tool: deterministic pipelines + LLM Agent, precise line-level comments, built-in multi-language ruleset (NPE, thread-safety, XSS, SQL injection), OpenAI &」。本文只整理倉庫可直接核對的內容，不把 star、Fork 或宣傳語當成品質證明。README 在「What is Open Code Review?」下寫到：Open Code Review is an AI-powered code review CLI tool. It originated as Alibaba Group's internal official AI code review assistant , over the past two years, it has served tens of thousands of developers and identified millions of code。這說明的是專案邊界，不是已完成的生產驗證。

從 README 的「The Problem with General-Purpose Agents」與相關條目，可以先判斷它是否處理你的實際問題：Position drift , Reported issues frequently don't match the actual code location, with line numbers or file references drifting off target.。若需求不同，不應只因專案熱度就採用。本文保留原始專案名、命令與元件名，方便回到一手來源核對。 README 另外列出一項可核對的資訊：Incomplete coverage , On larger changesets, agents tend to "cut corners," selectively reviewing only some files and missing others.。這類原文條目可用來設計試跑步驟，但不能取代實際環境測試。

README 將運作方式分散在「Benchmark」等段落。可確認的線索包括：> Compared to general-purpose agents (Claude Code), Open Code Review achieves significantly higher Precision and F1 with the same underlying model, while consuming only 1/9 of the tokens and completing reviews faster.。本文不把未寫出的架構、效能或安全邊界補成結論；真正的執行鏈仍要配合目錄、設定檔與版本標籤檢查。

第一次安裝應從 README 指出的入口開始。目前可核對的命令是： npm install -g @alibaba-group/open-code-review 如果倉庫沒有命令，本文不會自行編造步驟，而是建議先閱讀「Benchmark」，確認系統依賴、預設埠與首次初始化。

日常使用取決於專案文件。README 的「Benchmark」段落提到：A real-world code review benchmark built from 50 popular open-source repositories, 200 real Pull Requests, and 10 programming languages , cross-validated by 80+ senior engineers (1,505 annotated ground-truth issues).。設定檔、環境變數、權限與資料目錄只在來源明確時才會記錄；沒有寫出的預設值，應在測試環境驗證並保留回滾副本。 同一部分也提到：Unstable quality , Natural-language-driven Skills are hard to debug, and review quality fluctuates significantly with minor prompt variations.。